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Data Router

Community
MAGA2010
data-router

Classify any input path into one of eight modalities and emit a route manifest. First stage of data-master; no statistics, no cleaning.

Overview

PublisherMAGA2010
Repositorydata-master
Skill namedata-router
Stars
55
Forks
1
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by MAGA2010 on GitHub. Read the source before you install it.

Installation

Install the Data Router AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/MAGA2010/data-master/tree/main/skills/data-router
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MAGA2010/data-master.git /tmp/data-master
mkdir -p .claude/skills
cp -r /tmp/data-master/skills/data-router .claude/skills/data-router
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Data Router in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Data Router on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Data Router is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

data-router

Stage 1a of the data-master pipeline. The router in ../../SKILL.md owns the end-to-end run; this skill owns one stage and one gate. Read the parent contract before changing anything here: the invariants in ../../SKILL.md (additive-only, types decided once, default-FAIL gates, three-part provenance) are not restated, they are inherited.

When to invoke

The moment a user hands over a file, a folder, or a glob. Never skip it: a CSV with a timestamp column and a free-text corpus are both .csv/.txt, and the wrong branch produces a technically valid report about the wrong object.

Inputs

  • a path, folder, or glob
  • an optional --modality override, recorded as origin: user

Outputs

  • outputs/route.json -- one entry per input file: {path, modality, evidence, confidence, branch, alternatives_rejected}

Commands

powershell
# inspect what will be routed; prints the decision table without writing anything
python scripts/check_deps.py --explain

# the decision table itself
Get-Content references/modality-routing.md

Gate (default FAIL)

route.json exists and every input file has a modality in {tabular, text-corpus, time-series, image-set, audio-set, geospatial, mixed, unknown}. A file with modality: unknown routes to references/research-protocol.md and stops the automatic branch -- it does not silently fall back to tabular.

Pickle-based serialization (.pkl, .pickle, .joblib, .dill, .pck, .pckl, .pt, .pth) is explicitly blocked with blocked_reason: unsafe_deserialization. Never load it. For every unknown format, search only public format names; keep observed bytes, headers, metadata, paths, and records out of WebSearch and WebFetch.

Failure modes seen in real runs

  • A .csv of free text is routed to tabular, then every column is reported as categorical. Sniff the delimiter and the fraction of unique tokens per row before committing.
  • A timestamped table is routed to tabular, so the trend is reported as a static association. If a column parses as datetime and is monotonic or near-monotonic, route to time-series.
  • A glob silently matching zero files reports "no data" instead of failing the gate. Count matched files and fail loudly on zero.

Do not

  • do not infer modality from the extension alone;
  • do not let a mixed folder collapse into one modality -- route each file, then merge reports;
  • do not overwrite a user-supplied --modality; record it as an override with its evidence.

Upstream / downstream

  • next: ../data-profiler/SKILL.md
  • table: ../../references/modality-routing.md
  • unknown inputs: ../../references/research-protocol.md

Frequently asked questions

What does the Data Router AI skill do?

Classify any input path into one of eight modalities and emit a route manifest. First stage of data-master; no statistics, no cleaning.

Why use Data Router on TypingMind?

Because you install it once and use it with any model. Data Router is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Data Router in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MAGA2010/data-master/tree/main/skills/data-router. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Data Router?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Data Router?

As many as you like. As long as a model supports skills, you can use Data Router with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Data Router AI skill free?

Yes. It is published on GitHub by MAGA2010 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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